Data Engineer

Cerberus Capital Management; Greater London; On-site; GBP 60,000 - 100,000; Full time

Job summary

A financial services firm is seeking a Data Engineer to expand their capabilities in building modern, scalable data platforms. The role involves designing cloud-based data pipelines and utilizing tools such as dbt and Airflow. The ideal candidate will possess strong Python skills, experience with Azure, and an understanding of data warehousing with Snowflake. This position provides opportunities for impact within a small, agile team dedicated to optimizing data for advanced analytics and machine learning applications, promoting a collaborative and innovative culture.

Qualifications

• Hands-on experience in production environments emphasizing performance optimization.
• Advanced proficiency in Python for data engineering and pipeline development.
• Proven expertise with Snowflake in schema design and data ingestion.

Responsibilities

• Design and build scalable, cloud-based data pipelines and architectures.
• Develop ELT workflows using tools like dbt and SQL.
• Collaborate with data scientists to ensure data integration for analytics.

Skills

Python expertise

Cloud platforms (Azure)

Data modeling (dbt)

SQL databases (PostgreSQL, MySQL)

Workflow orchestration (Apache Airflow)

Infrastructure as code (Terraform, Pulumi)

Communication and problem-solving

Education

Degree in STEM field

Tools

Azure

Snowflake

Apache Airflow

Job description

About the job

We are looking to expand our Data Engineering team to build modern, scalable data platforms for our internal investment desks and portfolio companies. You will contribute to the firm’s objectives by delivering rapid and reliable data solutions that unlock value for Cerberus desks, portfolio companies, and other businesses. You’ll do this by designing and implementing robust data architectures, pipelines, and workflows that enable advanced analytics and AI applications. You may also support initiatives such as due diligence and pricing analyses by ensuring high-quality, timely data availability.

What you will do

• Design, build, and maintain scalable, cloud-based data pipelines and architectures to support advanced analytics and machine learning initiatives.
• Develop robust ELT workflows using tools like dbt, Airflow, and SQL (PostgreSQL, MySQL) to transform raw data into high-quality, analytics-ready datasets.
• Collaborate with data scientists, analysts, and software engineers to ensure seamless data integration and availability for predictive modeling and business intelligence.
• Optimize data storage and processing in Azure environments for performance, reliability, and cost-efficiency.
• Implement best practices for data modeling, governance, and security across all platforms.
• Troubleshoot and enhance existing pipelines to improve scalability and resilience.

Sample Projects You Work On

• Financial Asset Management Pipeline: Build and manage data ingestion from third‑party APIs, model data using dbt, and support machine learning workflows for asset pricing and prediction using Azure ML Studio. This includes ELT processes, data modeling, running predictions, and storing outputs for downstream analytics.

Your Experience

We’re a small, high‑impact team with a broad remit and diverse technical backgrounds. We don’t expect any single candidate to check every box below - if your experience overlaps strongly with what we do and you’re excited to apply your skills in a fast‑moving, real‑world environment, we’d love to hear from you.

• Strong technical foundation: Degree in a STEM field (or equivalent experience) with hands‑on experience in production environments, emphasizing performance optimization and code quality.
• Python expertise: Advanced proficiency in Python for data engineering, data wrangling and pipeline development.
• Cloud platforms: Hands‑on experience working with Azure. AWS experience is considered, however Azure exposure is essential.
• Data warehousing: Proven expertise with Snowflake – schema design, performance tuning, data ingestion, and security.
• Workflow orchestration: Production experience with Apache Airflow (Prefect, Dagster or similar), including authoring DAGs, scheduling workloads and monitoring pipeline execution.
• Data modeling: Strong skills in dbt, including writing modular SQL transformations, building data models, and maintaining dbt projects.
• SQL databases: Extensive experience with PostgreSQL, MySQL (or similar), including schema design, optimizationnega, and complex query development.
• Infrastructure as code: Production experience with declarative infrastructure definition – e.g. Terraform, Pulumi or similar.
• Version control and CI/CD: Familiarity with Git‑based workflows and continuous integration/deployment practices (experience with Azure DevOps or Github Actions) to ensure seamless code integration and deployment processes.
• Communication and problem‑solving skills: Ability to articulate complex technical concepts to technical and non‑technical stakeholders alike. Excellent problem‑solving skills with a strong analytical mindset.

About Us

We are a new, but growing team of AI specialists – data scientists, software engineers and technology strategists – working to transform how an alternative investment firm with $65B in assets under management leverages technology and data. Our remit is broad, spanning investment operations, portfolio companies and internal systems, giving the team the opportunity to shape the way the firm approaches analytics, automation and decision‑making.

We operate with the creativity and agility of a small team, tackling diverse, high‑impact challenges across the firm. While we are embedded within a global investment platform, we maintain a collaborative, innovative culture where our AI talent can experiment, learn and have real influence on business outcomes.

Job Details

• Recipes raid seniority level: Associate
• Employment type: Full‑time
• Industries: Financial Services, Investment Management, and Venture Capital and Private Equity Principals